A nomogram clinical prediction model for predicting urinary infection stones: development and validation in a retrospective study.

PURPOSE: This study aimed to develop a nomogram prediction model to predict the exact probability of urinary infection stones before surgery in order to better deal with the clinical problems caused by infection stones and take effective treatment measures. METHODS: We retrospectively collected the clinical data of 390 patients who were diagnosed with urinary calculi by imaging examination and underwent postoperative stone analysis between August 2018 and August 2023. The patients were randomly divided into training group (n = 312) and validation group (n = 78) using the "caret" R package. The clinical data of the patients were evaluated. Univariate and multivariate logistic regression analysis were used to screen out the independent influencing factors and construct a nomogram prediction model. The receiver operating characteristic curve (ROC), calibration curves, and decision curve analysis (DCA) and clinical impact curves were used to evaluate the discrimination, accuracy, and clinical application efficacy of the prediction model. RESULTS: Gender, recurrence stones, blood uric acid value, urine pH, and urine bacterial culture (P < 0.05) were independent predictors of infection stones, and a nomogram prediction model ( https://zhaoyshenjh.shinyapps.io/DynNomInfectionStone/ ) was constructed using these five parameters. The area under the ROC curve of the training group was 0.901, 95% confidence interval (CI) (0.865-0.936), and the area under the ROC curve of the validation group was 0.960, 95% CI (0.921-0.998). The results of the calibration curve for the training group showed a mean absolute error of 0.015 and the Hosmer-Lemeshow test P > 0.05. DCA and clinical impact curves showed that when the threshold probability value of the model was between 0.01 and 0.85, it had the maximum net clinical benefit. CONCLUSIONS: The nomogram developed in this study has good clinical predictive value and clinical application efficiency can help with risk assessment and decision-making for infection stones in diagnosing and treating urolithiasis.

Relation of poverty with treatment-seeking behavior and antibiotic misuse among UTI patients in Pakistan.

Objective: The current study aimed to assess the relation between multi-dimension poverty, treatment-seeking behavior, and antibiotic misuse among urinary tract infection (UTI) patients. Method: A cross-sectional approach was utilized to recruit patients who had a history of UTI in the previous month from two provinces of Pakistan. The treatment-seeking behavior and antibiotic misuse data were collected on a self-developed questionnaire, whereas the poverty data were collected on a modified multi-dimension poverty index (MPI). Descriptive statistics were applied to summarize the data. The logistic regression analysis was carried out to assess the association of multi-dimension poverty with patient treatment-seeking behavior and antibiotic misuse. Results: A total of 461 participants who had UTI symptoms in the previous month were recruited. Most of the participants in the severely deprived stage treated the UTI (p < 0.001); however, there was a high proportion of the participants who consulted with friends and family for UTI treatment (p < 0.001). The patients with deprivation status (deprived and severely deprived) were less associated with formal consultation. The poorer subgroups were less likely to practice antibiotic course completion. Conclusion: The current study highlighted that poverty plays an important role in antibiotic misuse. Poorer subgroups were associated with informal consultations and the incompletion of the antibiotic course. Further studies are needed to explore the potential role of poverty in treatment-seeking behavior and antibiotic misuse.

Assessing the utility of natural language processing for detecting postoperative complications from free medical text.

BACKGROUND: Postoperative complication rates are often assessed through administrative data, although this method has proven to be imprecise. Recently, new developments in natural language processing have shown promise in detecting specific phenotypes from free medical text. Using the clinical challenge of extracting four specific and frequently undercoded postoperative complications (pneumonia, urinary tract infection, sepsis, and septic shock), it was hypothesized that natural language processing would capture postoperative complications on a par with human-level curation from electronic health record free medical text. METHODS: Electronic health record data were extracted for surgical cases (across 11 surgical sub-specialties) from 18 hospitals in the Capital and Zealand regions of Denmark that were performed between May 2016 and November 2021. The data set was split into training/validation/test sets (30.0%/48.0%/22.0%). Model performance was compared with administrative data and manual extraction of the test data set. RESULTS: Data were obtained for 17 486 surgical cases. Natural language processing achieved a receiver operating characteristic area under the curve of 0.989 for urinary tract infection, 0.993 for pneumonia, 0.992 for sepsis, and 0.998 for septic shock, whereas administrative data achieved a receiver operating characteristic area under the curve of 0.595 for urinary tract infection, 0.624 for pneumonia, 0.571 for sepsis, and 0.625 for septic shock. CONCLUSION: The natural language processing approach was able to capture complications with acceptable performance, which was superior to administrative data. In addition, the model performance approached that of manual curation and thereby offers a potential pathway for complete real-time coverage of postoperative complications across surgical procedures based on natural language processing assessment of electronic health record free medical text.

The Diagnosis and Treatment of Adult Urinary Tract Infections in the Emergency Department.

Emergency medicine has been called the art of "making complicated clinical decisions with limited information." This description is particularly relevant in the case of diagnosis and treatment of urinary tract infections (UTIs). Although common, UTIs are often challenging to diagnose given the presence of non-specific signs and symptoms and over-reliance on laboratory findings. This review provides an interdisciplinary interpretation of the primary literature and practice guidelines, with a focus on diagnostic and antimicrobial stewardship in the emergency department.

Multidrug resistance among uropathogenic clonal group A E. Coli isolates from Pakistani women with uncomplicated urinary tract infections.

OBJECTIVE: Multi-drug resistance (MDR) has notably increased in community acquired uropathogens causing urinary tract infections (UTIs), predominantly Escherichia coli. Uropathogenic E. coli causes 80% of uncomplicated community acquired UTIs, particularly in pre-menopausal women. Considering this high prevalence and the potential to spread antimicrobial resistant genes, the current study was conducted to investigate the presence of clinically important strains of E. coli in Pakistani women having uncomplicated cystitis and pyelonephritis. Women belonging to low-income groups were exclusively included in the study. Seventy-four isolates from urine samples were processed, phylotyped, and screened for the presence of two Single Nucleotide Polymorphisms (SNPs) particularly associated with a clinically important clonal group A of E. coli (CgA) followed by antibiotic susceptibility testing and genome sequence analysis. RESULTS: Phylogroup B2 was most prevalent in patients and 44% of isolates were positive for the presence of CgA specific SNPs in Fumarate hydratase and DNA gyrase subunit B genes. Antibiotic susceptibility testing showed widespread resistance to trimethoprim-sulfamethoxazole and extended-spectrum beta-lactamase production. The infection analysis revealed the phylogroup B2 to be more pathogenic as compared to the other groups. The genome sequence of E. coli strain U17 revealed genes encoding virulence, multidrug resistance, and host colonization mechanisms. CONCLUSIONS: Our research findings not only validate the significant occurrence of multidrug-resistant clonal group A E. coli (CgA) in premenopausal Pakistani women suffering from cystitis and pyelonephritis but also reveal the presence of genes associated withvirulence, and drug efflux pumps. The detection of highly pathogenic, antimicrobial-resistant phylogroup B2 and CgA E. coli strains is likely to help in understanding the epidemiology of the pathogen and may ultimately help to reduce the impact of these strains on human health. Furthermore, the findings of this study will particularly help to reduce the prevalence of uncomplicated UTIs and the cost associated with their treatment in women belonging to low-income groups.

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection.

Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are among the most prevalent infectious diseases worldwide, with a notable increase in treatment costs due to the emergence of drug-resistant pathogens. Current diagnostic strategies for UTIs, such as urine culture and flow cytometry, require time-consuming protocols and expensive equipment. We present here a machine learning-assisted colorimetric sensor array based on recognition of ligand-functionalized Fe single-atom nanozymes (SANs) for the identification of microorganisms at the order, genus, and species levels. Colorimetric sensor arrays are built from the SAN Fe1-NC functionalized with four types of recognition ligands, generating unique microbial identification fingerprints. By integrating the colorimetric sensor arrays with a trained computational classification model, the platform can identify more than 10 microorganisms in UTI urine samples within 1 h. Diagnostic accuracy of up to 97% was achieved in 60 UTI clinical samples, holding great potential for translation into clinical practice applications.

Antibiotic Switches in Urinary Tract Infection Are Associated With Atypical Symptoms and Emergent Care.

IMPORTANCE: Given worsening global antibiotic resistance, antimicrobial stewardship aims to use the shortest effective duration of the most narrow-spectrum, effective antibiotic for patients with specific urinary symptoms and laboratory testing consistent with urinary tract infection (UTI). Inappropriate treatment and unnecessary antibiotic switching for UTIs harms patients in a multitude of ways. OBJECTIVE: This study sought to analyze antibiotic treatment failures as measured by antibiotic switching for treatment of UTI in emergent and ambulatory care. STUDY DESIGN: For this retrospective cohort study, 908 encounters during July 2019 bearing a diagnostic code for UTI/cystitis in a single health care system were reviewed. Urinary and microbiological testing, symptoms endorsed at presentation, and treatments prescribed were extracted from the medical record. RESULTS: Of 908 patients diagnosed with UTI, 64% of patients (579/908) received antibiotics, 86% of which were empiric. All patients evaluated in emergent care settings were prescribed antibiotics empirically in contrast to 71% of patients in ambulatory settings (P < 0.001). Of patients given antibiotics, 89 of 579 patients (15%, 10% of all 908 patients) were switched to alternative antibiotics within 28 days. Emergent care settings and positive urine cultures were significantly associated with increased antibiotic switching. Patients subjected to switching tended to have higher rates of presenting symptoms inconsistent with UTI. CONCLUSIONS: Empiric treatment, particularly in an emergent care setting, was frequently inappropriate and associated with increasing rates of antibiotic switching. Given the profound potential contribution to antibiotic resistance, these findings highlight the need for improved diagnostic and prescribing accuracy for UTI.

Rate of Urinary Tract Infections, Bacteremia, and Meningitis in Preterm and Term Infants.

BACKGROUND AND OBJECTIVES: There are very limited data on the rate of urinary tract infections (UTI), bacteremia, and meningitis in preterm infants with fever. Many of the studies on the incidence of these infections excluded preterm infants. This study compared the rate of these infections in preterm infants born at 32-36 weeks to term infants born at 37-42 weeks. METHODS: A multicenter observational cohort study was conducted to evaluate rates of UTI, bacteremia, and meningitis in term and preterm infants 8-60 days of age with a diagnosis of fever from 2016 through 2022 using encounter data from children's hospitals in the Pediatric Health Information System. RESULTS: There were 19 507 total febrile infants identified, of which 2162 were preterm and 17 345 were term. Preterm infants had a lower rate of UTI than term infants (1.8% confidence interval [CI] [1.3-2.5] vs 3.0% CI [2.7-3.2], P = .001). Preterm and term infants did not have statistically different rates of bacteremia (1.5% CI [1.3-1.7] vs 1.2% CI [0.8-1.8], P = .44) or meningitis (0.16% CI [0.1-0.2] vs 0.05% CI [0-0.2], P = .36). CONCLUSIONS: There was no difference in the rate of bacteremia or meningitis between term and preterm infants in a large multicenter cohort of febrile infants. Preterm infants had a lower rate of UTI than term infants. This is the first multicenter study to compare UTI, bacteremia, and meningitis between term and preterm febrile infants.

Dipsticks and point-of-care Microscopy to reduce antibiotic use in women with an uncomplicated Urinary Tract Infection (MicUTI): protocol of a randomised controlled pilot trial in primary care.

INTRODUCTION: Uncomplicated urinary tract infections (uUTIs) in women are common infections encountered in primary care. Evidence suggests that rapid point-of-care tests (POCTs) to detect bacteria and erythrocytes in urine at presentation may help primary care clinicians to identify women with uUTIs in whom antibiotics can be withheld without influencing clinical outcomes. This pilot study aims to provide preliminary evidence on whether a POCT informed management of uUTI in women can safely reduce antibiotic use. METHODS AND ANALYSIS: This is an open-label two-arm parallel cluster-randomised controlled pilot trial. 20 general practices affiliated with the Bavarian Practice-Based Research Network (BayFoNet) in Germany were randomly assigned to deliver patient management based on POCTs or to provide usual care. POCTs consist of phase-contrast microscopy to detect bacteria and urinary dipsticks to detect erythrocytes in urine samples. In both arms, urine samples will be obtained at presentation for POCTs (intervention arm only) and microbiological analysis. Women will be followed-up for 28 days from enrolment using self-reported symptom diaries, telephone follow-up and a review of the electronic medical record. Primary outcomes are feasibility of patient enrolment and retention rates per site, which will be summarised by means and SDs, with corresponding confidence and prediction intervals. Secondary outcomes include antibiotic use for UTI at day 28, time to symptom resolution, symptom burden, number of recurrent and upper UTIs and re-consultations and diagnostic accuracy of POCTs versus urine culture as the reference standard. These outcomes will be explored at cluster-levels and individual-levels using descriptive statistics, two-sample hypothesis tests and mixed effects models or generalised estimation equations. ETHICS AND DISSEMINATION: The University of Würzburg institutional review board approved MicUTI on 16 December 2022 (protocol n. 109/22-sc). Study findings will be disseminated through peer-reviewed publications, conferences, reports addressed to clinicians and the local citizen's forums. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT05667207.

Should you test for urinary tract infection in children with respiratory symptoms?

QUESTION: An 8-month-old boy presented to our clinic with a 3-day history of fever. He has had a cough and rhinorrhea since the onset of the fever, and his 4-year-old sibling has recently had cough and cold symptoms. I have heard that the presence of respiratory symptoms means that urinary tract infection (UTI) is less likely. In infants with fever and respiratory symptoms, who should have a sample collected for urinalysis for UTI? ANSWER: The approach to diagnosing febrile infants who have respiratory symptoms varies by age. Urinalysis should be done for all febrile infants younger than 2 months of age, regardless of whether they have respiratory symptoms. Clinicians should assess risk factors for UTI in every infant between 2 and 24 months of age and should not exclude the diagnosis of UTI based on respiratory symptoms alone. Use of a predictive tool to estimate the pretest probability of UTI would aid decision making about patients in this population.

Asymptomatic bacteriuria prior to partial and radical nephrectomy: To screen or not to screen? Results from the national and multicenter TOCUS database.

INTRODUCTION: In the era of increased bacterial resistance, the main strategy is to reduce the prescription of antibiotics when possible. Nowadays, it is highly recommended to screen for asymptomatic bacteriuria (ABU), prior to urological surgery with potential mucosal breach or urine exposure. Screening and treating urinary colonization is a strategy widely adopted before radical and partial nephrectomy but without any evidence. Our main end point in this study is to analyze the relationship between preoperative urine culture and the risk of postoperative febrile urinary tract infection (UTI) or surgical-site infection (SSI) in partial or radical nephrectomy patients. METHODS: We conducted a multicenter retrospective cohort study between January 2016 and January 2023 in 11 French tertiary referral hospitals (TOCUS database). We collected the data for 269 patients including several pre-, intra-, and post-operative variables that could potentially increase the risk of postoperative UTI and SSI including preoperative urinary culture results. RESULTS: The incidence rate of postoperative UTI and SSI was 8.9% in our study. After conducting a logistic multivariate analysis, a propensity score matching analysis, and a subgroup analysis, we found no significant correlation between the urine culture and the postoperative UTI risk [OR = 1.2 (0.5-2.7) (p = 0.7)]. Only the postoperative non-infectious complications were related to a higher risk of postoperative UTI [OR = 12 (4-37), p < 0.001)]. CONCLUSION: Our research shows that screening and treating for ABU prior to radical or partial nephrectomy seems to be unnecessary to prevent postoperative UTI and SSI.

Unraveling the complex relationship: Multiple sclerosis, urinary tract infections, and infertility.

BACKGROUND: Multiple sclerosis (MS) is an immune system disorder that affects the central nervous system (CNS) and progressively damages nerve fibers and protective myelin. People with MS often experience a wide range of complications, including lower urinary tract dysfunction, urinary tract infections (UTIs) and sexual dysfunction. MS is common in young people and can lead to sexual dysfunction (SD) and infertility, which becomes more pronounced as the disease progresses. RESULTS: Over the past two decades, significant advances have been made in the management of MS, which may slow the progression of the disease and alter its course. However, UTI and SD remain significant challenges for these patients. Awareness of the underlying complications of MS, such as UTIs and infertility, is crucial for prevention, early detection and appropriate treatment, as there is a causal relationship between UTIs and the use of corticosteroids during an attack. CONCLUSION: This article provides an overview of potential microbial pathogens that contribute to the development of MS, as well as an assessment of people with MS who report UTIs and infertility.

Acute Uncomplicated UTIs in Adults: Rapid Evidence Review.

An acute uncomplicated urinary tract infection (UTI) is a bacterial infection of the lower urinary tract with no sign of systemic illness or pyelonephritis in a noncatheterized, nonpregnant adult with no urologic abnormalities or immunocompromise. In women, a self-diagnosis of a UTI with the presence of typical symptoms (e.g., frequency, urgency, dysuria/burning sensation, nocturia, suprapubic pain), without vaginal discharge, is accurate enough to diagnose an uncomplicated UTI without further testing. Urine culture and susceptibility testing should be reserved for women with recurrent infection, treatment failure, history of resistant isolates, or atypical presentation to make a definitive diagnosis and guide antibiotic selection. First-line antibiotics include nitrofurantoin for five days, fosfomycin in a single dose, trimethoprim for three days, or trimethoprim/sulfamethoxazole for three days. Symptomatic treatment with nonsteroidal anti-inflammatory drugs and delayed antibiotics may be considered because the risk of complications is low. Increased fluids, intake of cranberry products, and methenamine hippurate can prevent recurrent infections. Antibiotic prophylaxis is also effective in preventing recurrence but has a risk of adverse effects and antimicrobial resistance. Men with lower UTI symptoms should always receive antibiotics, with urine culture and susceptibility results guiding the antibiotic choice. Clinicians should also consider the possibility of urethritis and prostatitis in men with UTI symptoms. First-line antibiotics for men with uncomplicated UTI include trimethoprim, trimethoprim/sulfamethoxazole, and nitrofurantoin for seven days. Uncomplicated UTIs in nonfrail women and men 65 years and older with no relevant comorbidities also necessitate a urine culture with susceptibility testing to adjust the antibiotic choice after initial empiric treatment; first-line antibiotics and treatment durations do not differ from those recommended for younger adults.

Standardization of urinary tract infection diagnosis in the neonatal ICU: Experience at a tertiary care center.

BACKGROUND: Urinary tract infections (UTIs) and antibiotic overexposure are common neonatal problems. Recently, evidence has emerged that a standardized approach to neonatal UTI can reduce unnecessary diagnosis without complications. This quality improvement project aimed to achieve those goals in our neonatal intensive care unit (NICU). METHODS: A UTI diagnosis guideline was adapted from the literature with the goal of maximizing the proportion of diagnosed UTIs that conform to accepted diagnostic criteria: >10,000 CFU/mL of one organism with pyuria, or >50,000 CFU/mL of one organism regardless of pyuria. The guideline was implemented in a level III NICU. Adherence, results, and complications were monitored for 12 months. RESULTS: Guideline adherence after implementation was favorable, as evidenced by increased adoption of urinalysis with microscopy. There was a non-significant increase in diagnostic adherence to criteria, 87% to 93%, and non-significant decrease in the rate of UTI diagnosis, 39% to 36%. Complications were not significantly changed. Most UTIs were due to gram-negative rods, especially E. coli; Enterococcus was a common contaminant. CONCLUSIONS: A guideline for diagnosing UTIs can safely increase uniformity. In contrast to previously published results, no significant changes were seen in the rate of UTI or the proportion of diagnoses conforming to the criteria for UTI. It is likely that guideline effects depend on the established practices of NICU providers. Additionally, a consistent pattern was seen in which organisms were more likely to be judged the source of true UTIs or contaminated cultures, meriting further study.

A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection.

Urinary tract infection (UTI) is a common disorder. Its diagnosis can be made by microscopic examination of voided urine for markers of infection. This manual technique is technically difficult, time-consuming and prone to inter-observer errors. The application of computer vision to this domain has been slow due to the lack of a clinical image dataset from UTI patients. We present an open dataset containing 300 images and 3,562 manually annotated urinary cells labelled into seven classes of clinically significant cell types. It is an enriched dataset acquired from the unstained and untreated urine of patients with symptomatic UTI using a simple imaging system. We demonstrate that this dataset can be used to train a Patch U-Net, a novel deep learning architecture with a random patch generator to recognise urinary cells. Our hope is, with this dataset, UTI diagnosis will be made possible in nearly all clinical settings by using a simple imaging system which leverages advanced machine learning techniques.

Diagnostic and treatment patterns in urinary and genital tract infections: insights from a referral clinic in Beirut, Lebanon.

BACKGROUND: Urinary Tract Infections (UTIs) and Genital Tract Infections (GTIs) are common yet serious health concerns. Precise diagnosis is crucial due to the potential severe consequences of misdiagnosis. This study aims to distinguish between UTIs and GTIs, highlighting the importance of accurate differentiation. MATERIALS AND METHODS: The study encompassed 294 patients, categorized into 4 groups: Group GNI (no infection, N = 57), Group GUI (urinary infection, N = 52), Group GGI (genital infection, N = 139), and Group GGUI (both infections, N = 46). Methods included patient interviews, clinical examinations, and laboratory tests such as urine and vaginal swab cultures. RESULTS: The investigation revealed no significant differences in age, BMI, residency, or nationality across groups. However, socioeconomic status varied, with Group GNI having the lowest proportion of low socioeconomic status. In obstetrical characteristics, non-pregnancy rates were higher in Groups GUI and GGUI, with GGUI showing a notably higher abortion rate. Symptom analysis indicated lower symptom prevalence in Group GNI, with pain, itching, pruritus, and vaginal discharge being less frequent, suggesting a link between infection presence and symptom severity. Treatment patterns showed higher usage of ciprofloxacin, antifungals, and vaginal tablets in Groups GUI and GGUI. Laboratory findings highlighted significant Leucocyte Esterase presence and variations in WBC and RBC counts, particularly in Group GGUI. CONCLUSION: The study emphasizes the need for advanced diagnostic techniques, especially those focusing on individual microbial patterns, to enhance UGTI diagnosis. Variations in symptom presentation and treatment across groups underline the necessity for personalized diagnostic and treatment strategies.

Concentration of novel urinary tract infection biomarkers in neonates.

Urinary tract infections (UTIs) are a common comorbidity in hospitalized neonates. The current UTI diagnostics have several limitations including invasive collection of urinary samples to ensure sterility, risk of contamination and lack of consensus definitions of UTI based on urine culture. Antimicrobial peptides (AMPs) have been recently utilized as novel biomarkers that can efficiently and accurately diagnose pediatric UTI. However, the concentration of AMPs in neonatal urine is not well-defined. Urine from neonates admitted to a single level IV neonatal intensive care unit was obtained to determine baseline concentration of two AMPs, Ribonuclease 7 (RNase 7) and Beta Defensin-1 (BD-1) and to define the relationship between AMP concentration and gestational age (GA). AMP levels were normalized to urine creatinine. RNase 7 and BD-1 were expressed in neonatal urine (n = 66) regardless of GA and as early as 22 weeks gestation. Urinary concentrations of both AMPs decreased as GA and birthweight increased. The overall median urinary RNase 7/UCr and BD-1/UCr values were 271 ng/mg, and 116 ng/mg, respectively. Median urinary concentrations of RNase 7/UCr for infants born at < 27, 27-32, 33-35 and ≥ 36 weeks were 569, 308, 254, and 124 ng/mg respectively. Similarly, the concentrations of BD-1/UCr at these GA were 166, 115, 108, and 14 ng/mg, respectively. Baseline neonatal urinary concentration of two AMPs (RNase 7 and BD-1) and the variation by GA were identified. This is an essential first step toward the potential utilization of AMPs in improving neonatal UTI diagnostics.